




'''simple docstring'''




import heapq as hq
import math
from collections.abc import Iterator






class      UpperCAmelCase_     :


	"""simple docstring"""


	def __init__(						self						, UpperCAmelCase_				):
						snake_case_	=      str(id_				)
						snake_case_	=      None
						snake_case_	=      None
						snake_case_	=      []
						snake_case_	=      {}  # {vertex:distance}







	def __lt__(						self						, UpperCAmelCase_				):
						return self.key < other.key







	def __repr__(						self				):
						return self.id







	def  _lowercase    (						self						, UpperCAmelCase_				):
						self.neighbors.append(UpperCamelCase__				)







	def  _lowercase    (						self						, UpperCAmelCase_						, UpperCAmelCase_				):
						snake_case_	=      weight



def      __snake_case       (   lowercase   :							Optional[int]			, lowercase   :							Dict			, lowercase   :							List[str]			, lowercase   :							Optional[Any]  ):
					graph[a - 1].add_neighbor(graph[b - 1]  )
					graph[b - 1].add_neighbor(graph[a - 1]  )
					# add the edges:
					graph[a - 1].add_edge(graph[b - 1]			, lowercase_  )
					graph[b - 1].add_edge(graph[a - 1]			, lowercase_  )
def      __snake_case       (   lowercase   :							list			, lowercase   :							Vertex  ):
					snake_case_	=      []
					for u in graph:
										snake_case_	=      math.inf
										snake_case_	=      None
					snake_case_	=      0
					snake_case_	=      graph[:]
					while q:
										snake_case_	=      min(lowercase_  )
										q.remove(lowercase_  )
										for v in u.neighbors:
															if (v in q) and (u.edges[v.id] < v.key):
																				snake_case_	=      u
																				snake_case_	=      u.edges[v.id]
					for i in range(1			, len(lowercase_  )  ):
										a.append((int(graph[i].id  ) + 1, int(graph[i].pi.id  ) + 1)  )
					return a
def      __snake_case       (   lowercase   :							list			, lowercase   :							Vertex  ):




					for u in graph:
										snake_case_	=      math.inf
										snake_case_	=      None
					snake_case_	=      0

					snake_case_	=      list(lowercase_  )
					hq.heapify(lowercase_  )

					while h:
										snake_case_	=      hq.heappop(lowercase_  )
										for v in u.neighbors:
															if (v in h) and (u.edges[v.id] < v.key):
																				snake_case_	=      u
																				snake_case_	=      u.edges[v.id]
																				hq.heapify(lowercase_  )

					for i in range(1			, len(lowercase_  )  ):
										yield (int(graph[i].id  ) + 1, int(graph[i].pi.id  ) + 1)
def      __snake_case       (   ):
					pass






if __name__ == "__main__":
					import doctest

					doctest.testmod()













'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowerCAmelCase        =							{"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __lowerCAmelCase        =							["GLPNFeatureExtractor"]
  __lowerCAmelCase        =							["GLPNImageProcessor"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __lowerCAmelCase        =							[
      "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST",
      "GLPNForDepthEstimation",
      "GLPNLayer",
      "GLPNModel",
      "GLPNPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_glpn import GLPNFeatureExtractor
    from .image_processing_glpn import GLPNImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_glpn import (
        GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
        GLPNForDepthEstimation,
        GLPNLayer,
        GLPNModel,
        GLPNPreTrainedModel,
    )


else:
  import sys

  __lowerCAmelCase        =							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




